Structural Optimization with Genetic Algorithm in Fire Situations: Innovation at the Service of Sustainability

Objective: The objective of this study is to develop a computational interface to optimize the cross-section of ribbed slabs in normal and fire situations, with the aim of achieving maximum functionality and safety at minimum cost, following normative prescriptions. Theoretical Framework: Structural optimization techniques stand out as innovative tools that promote the rational use of materials, enabling the reduction of consumption of resources such as concrete and steel, which, in turn, results in a lower environmental impact and cost reduction. Method: The methodology adopted for this research was to implement a slab optimization program in MATLAB, using the Genetic Algorithms (GA) method. Comparing the consumption of concrete and steel in the design. Results and Discussion: The results obtained revealed [synthesize the main results of the research]. In the discussion section, these results are contextualized in light of the theoretical framework, highlighting the implications and relationships identified. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: Genetic algorithm-based structural optimization is establishing itself as an innovation that promotes sustainability in structural engineering under fire conditions. The adopted approach contributes to the advancement of structural modeling aimed at reducing environmental impacts in civil construction. Originality/Value: The research stands out for integrating evolutionary methods into the design of structural elements with fire resistance requirements, promoting the achievement of more efficient solutions from a mechanical, economic and environmental point of view.